It's pretty cool to watch emerging technology rise to fame. It usually ends by being kicked to the curb pretty sharpish or becoming a staple in business innovation for the next few decades.
Gartner Hype Cycle.
Gartner Hype Cycle came to be in 1995 and has since become a widely recognised tool for technology trend analysis.
The Hype Cycle is just one of many market analysis tools available to understand a market's state.
Many of us trust it as the source of truth, a reliable way to make decisions about our technology and investments in business.
According to The Hype Cycle, emerging tech goes through five stages.
Stage 1: Technology Trigger. This is the part with the initial media attention.
Stage 2: In the Peak of Inflated Expectations, emerging tech is the talk everywhere, and predictions become wild and unrealistic!
Stage 3: Trough of Disillusionment. Investors and the public lose faith in the technology when it can't meet unrealistic demands. Remember self-driving? That nose-dived into the trough after reaching peak expectations; It had a lot of practical challenges to overcome before becoming a stable, widespread technology.
Stage 4: Slope of Enlightenment: The technology becomes better understood in this stage, and its potential benefits and limitations are more clearly defined.
Stage 5: Plateau of Productivity: Finally, it reaches mainstream adoption and delivers significant business value!
Specific AI technologies are expected to reach the plateau of productivity within two to five years.
There are many AI-driven technologies within Gartner Hype Cycle, and it is almost impossible to predict when one will reach maturity.
The latest AI Hype Cycle (shown above) is a well-researched estimate of what to expect over the next few years; we know that there are 14 AI-based technologies expected to reach the mainstream (the plateau) within two to five years. Those are:
Physics-informed AI, data-centric AI, Decision Intelligence, Composite AI, AI TRiSM, Generative AI, Synthetic Data, Edge AI, Digital Ethics, AI Maker and Teaching Kits, AI Cloud Services, Deep Learning, Intelligent Applications, Data Labeling and Annotation and Computer Vision. (If you want to know more about AI technologies set to mature within the next five years, this is your next read)
Eventually, all AI-related tech will plateau or stay stuck in the trough.
So, AI is in the peak, trough and plateau simultaneously?
AI is at every stage all at once, so it is calm, stable, mature and in its infancy.
You can know where specific AI technology is in its cycle by monitoring industry news and publications, keeping up-to-date with the magic quadrant, asking industry experts, or conducting research.
What AI-led technologies are mature?
Arguably, quite a few have reached the plateau of productivity. One example is Intelligent Applications.
Intelligent Applications, or "I-Apps" (positioned in the slope of enlightenment phase in the above image 2022), is arguably a mature tech; they use 'real-time and historical user data to make relevant and valuable user predictions and deliver adaptive and personalised user experiences' - itmunch.com.
Intelligent Applications are used at scale and powering some pretty hefty ROI-type stuff. According to a recent survey by Accenture, a Middle East-based telco uses AI-driven virtual assistants - which can communicate in different Arab dialects and in English - to handle 1.65 million customer calls each month. That's fewer calls to worry about for…whatever company that is.
Tech, like I-Apps, has reached the plateau and has become widely adopted and a must-have tool for businesses to operate efficiently while cutting costs.
Just look at ecommerce, social media and cloud computing. They were once wildly outrageous emerging technologies brought to our attention in the Gartner Hype Cycle. Now they're an essential part of how we live and do business.
Where is the AI hype focused right now?
There is AI technology that is mature enough to be adopted by the world's leading organisations, and there's stuff that the masses still aren't quite ready for.
Organisations are embracing mature AI technology because it's returning investments by the bucket load. These early successes (reported in a recent Accenture study) are shaping AI into a "value driver", so it's unsurprising that AI transformations are expected to happen quicker than digital transformations.
Source: Accenture research
What we're witnessing now, and for the next few years, is the peaks, troughs and steady incline of many elements of overall AI technology.
As specific AI technologies mature, we'll look less at new advancements and more at our own AI strategies or levels of "AI maturity".
Looking inwardly at how companies approach responsible AI, AI training and whether to build custom AI or go straight out of the box.
It's important to remember, though, Gartner isn't a crystal ball (although that would be rather helpful). Many factors will influence how things pan out with AI, including market demands, competition and regulatory red tape. Only time will tell.
We'd love to chat if you're interested in how AI could help your digital project.